Dataset Information

Quantitative analysis of breast tumours aided by three-dimensional photoacoustic/ultrasound functional imaging.

ABSTRACT: In this pilot study, we explored a quantitative method to analyse characteristics of breast tumours using 3D volumetric data obtained from a three-dimensional (3D) photoacoustic/ultrasound (PA/US) functional imaging system. Imaging results from 24 Asian patients with maximum tumour diameters less than 2?cm, including 8 benign tumours, 16 T1 stage invasive breast cancers (IBCs), and 22 normal breasts, were analysed. We found that the volumetric mean oxygenation saturation (SO₂) in tumour regions of T1 stage IBCs was 7.7% lower than that of benign tumours (P?=?0.016) and 3.9% lower than that of healthy breasts (P?=?0.010). The volumetric mean SO₂ in tumour surrounding regions of T1 stage IBCs was 4.9% lower than that of benign tumours (P?=?0.009). For differentiating T1 stage IBCs and benign tumours, with a cut-off SO₂ value of 78.2% inside tumours, we obtained a sensitivity of 100%, a specificity of 62.5%, and an AUC of 0.81; with a cut-off SO₂ value of 77.9% in regions surrounding tumours, we obtained a sensitivity of 100%, a specificity of 75% and an AUC of 0.84. Our preliminary results demonstrate that 3D PA/US functional imaging has the potential to provide valuable quantitative physiological information that may be useful for the detection and evaluation of breast tumours.

SUBMITTER: Yang M

PROVIDER: S-EPMC7229157 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Quantitative analysis of breast tumours aided by three-dimensional photoacoustic/ultrasound functional imaging.

Yang Meng M Zhao Lingyi L Yang Fang F Wang Ming M Su Na N Zhao Chenyang C Gui Yang Y Wei Yao Y Zhang Rui R Li Jianchu J Han Tao T He Xujin X Zhu Lei L Wu Huanwen H Li Changhui C Jiang Yuxin Y

Scientific reports 20200515 1

In this pilot study, we explored a quantitative method to analyse characteristics of breast tumours using 3D volumetric data obtained from a three-dimensional (3D) photoacoustic/ultrasound (PA/US) functional imaging system. Imaging results from 24 Asian patients with maximum tumour diameters less than 2 cm, including 8 benign tumours, 16 T1 stage invasive breast cancers (IBCs), and 22 normal breasts, were analysed. We found that the volumetric mean oxygenation saturation (SO<sub>2</sub>) in tumo ...[more]

PMID: 32415203

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Project description:SignificancePhotoacoustic tomography (PAT) has great potential in monitoring disease progression and treatment response in breast cancer. However, due to variations in breast repositioning, there is a chance of geometric misalignment between images. Further, poor repositioning can affect light fluence distribution and imaging field-of-view, making images different from one another. The net effect is that it becomes challenging to distinguish between image changes due to repositioning effects and those due to true biological variations.AimThe aim is to develop a three-dimensional image registration framework for geometrically aligning repeated PAT volumetric images, which are potentially affected by repositioning effects such as misalignment, changed radiant exposure conditions, and different fields-of-view.ApproachThe proposed framework involves the use of a coordinate-based neural network to represent the displacement field between pairs of PAT volumetric images. A loss function based on normalized cross correlation and Frangi vesselness feature extraction at multiple scales was implemented. We refer to our image registration framework as MUVINN-reg, which stands for multiscale vesselness-based image registration using neural networks. The approach was tested on a longitudinal dataset of healthy volunteer breast PAT images acquired with the hybrid photoacoustic-ultrasound Photoacoustic Mammoscope 3 imaging system. The registration performance was also tested under unfavorable repositioning conditions such as intentional mispositioning, and variation in breast-supporting cup size between measurements.ResultsA total of 13 pairs of repeated PAT scans were included in this study. MUVINN-reg showed excellent performance in co-registering each pair of images. The proposed framework was shown to be robust to image intensity shifts and field-of-view changes. Furthermore, MUVINN-reg could align vessels at imaging depths greater than 4 cm.ConclusionsThe proposed framework will enable the use of PAT for quantitative and reproducible monitoring of disease progression and treatment response.

Dataset Information

Quantitative analysis of breast tumours aided by three-dimensional photoacoustic/ultrasound functional imaging.

Publications

Quantitative analysis of breast tumours aided by three-dimensional photoacoustic/ultrasound functional imaging.

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